Traffic generators are commonly utilized in generating data traffic having characteristics suitable for testing a given communication system design. Such traffic generators may be implemented in hardware or software. Data traffic characteristics such as the time distribution of packet arrival are critical for testing communication system performance parameters such as buffering and scheduling capacity. It is generally desirable for the traffic generator to provide data traffic output which closely models the “real-life” behavior of packet arrival timing in the system. For example, such behavior often involves so-called burst arrival, when a certain number of packets arrive substantially back-to-back, that is, one after another without any significant intervening time between arriving packets.
In order to provide proper stress testing of the components of a communication system, in a system design phase or otherwise, a traffic generator should incorporate an efficient and accurate burst model. Unfortunately, conventional traffic generators typically utilize burst techniques, such as constant burst or probabilistic burst, that fail to provide adequate levels of efficiency and accuracy. As a result, such traffic generators do not provide sufficiently close modeling of “real-life” packet arrival behavior in a communication system.
Although other burst modeling techniques are known in the context of queuing theory, such techniques are often not readily applicable for use in practical hardware or software traffic generators. One such technique is the Hurst parameter, which has been used to describe burst behavior in theoretical network traffic description as well as in predicting natural burst events such as floods. Additional details can be found in, for example, W. Stallings, “High Speed Networks and Internets: Performance and Quality of Service,” Chapter 9, and W. E. Leland, “On the Self-Similar Nature of Ethernet Traffic,” IEEE/ACM Transactions on Networking, February 1994. However, the Hurst parameter is mathematically very complex, and therefore difficult to understand and formulate. In addition, it exhibits a computational complexity which makes it highly impractical to implement in a hardware or software traffic generator.
Accordingly, a need exists in the art for a traffic generator which provides improved modeling of burst arrival, in a manner that overcomes the disadvantages of the conventional techniques noted above.